10,804 research outputs found

    Basic kinetic wealth-exchange models: common features and open problems

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    We review the basic kinetic wealth-exchange models of Angle [J. Angle, Social Forces 65 (1986) 293; J. Math. Sociol. 26 (2002) 217], Bennati [E. Bennati, Rivista Internazionale di Scienze Economiche e Commerciali 35 (1988) 735], Chakraborti and Chakrabarti [A. Chakraborti, B. K. Chakrabarti, Eur. Phys. J. B 17 (2000) 167], and of Dragulescu and Yakovenko [A. Dragulescu, V. M. Yakovenko, Eur. Phys. J. B 17 (2000) 723]. Analytical fitting forms for the equilibrium wealth distributions are proposed. The influence of heterogeneity is investigated, the appearance of the fat tail in the wealth distribution and the relaxation to equilibrium are discussed. A unified reformulation of the models considered is suggested.Comment: Updated version; 9 pages, 5 figures, 2 table

    The Third Way on Objective Probability: A Skeptic's Guide to Objective Chance

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    The goal of this paper is to sketch and defend a new interpretation or theory of objective chance, one that lets us be sure such chances exist and shows how they can play the roles we traditionally grant them. The subtitle obviously emulates the title of Lewis seminal 1980 paper A Subjectivist s Guide to Objective Chance while indicating an important difference in perspective. The view developed below shares two major tenets with Lewis last (1994) account of objective chance: (1) The Principal Principle tells us most of what we know about objective chance; (2) Objective chances are not primitive modal facts, propensities, or powers, but rather facts entailed by the overall pattern of events and processes in the actual world. But it differs from Lewis’ account in most other respects. Another subtitle I considered was A Humean Guide ... But while the account of chance below is compatible with any stripe of Humeanism (Lewis , Hume s, and others ), it presupposes no general Humean philosophy. Only a skeptical attitude about probability itself is presupposed (as in point (2) above); what we should say about causality, laws, modality and so on is left a separate question. Still, I will label the account to be developed “Humean objective chance”

    The propensity function as formal passkey to economic action

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    The purpose of the present paper is to demonstrate how the interaction of the structural axiomatic core and the behavioral propensity function produces plausible outcomes in the product market. The propensity function is a compact formal expression of random, semi-random, and deterministic behavioral assumptions. Its two components are direction and magnitude of the rate of change of an elementary axiomatic variable. A type-C propensity function is the formal container for a familiar conception that Samuelson identified as qualitative prediction. Two type-C functions are sufficient to produce stochastic stability and optimality in the product market.New framework of concepts; Structure-centric; Axiom set; Qualitative prediction; Tendency laws; Separability; Determinism–indeterminism; Information function; Action function

    After the games are over: life-history trade-offs drive dispersal attenuation following range expansion.

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    Increased dispersal propensity often evolves on expanding range edges due to the Olympic Village effect, which involves the fastest and fittest finding themselves together in the same place at the same time, mating, and giving rise to like individuals. But what happens after the ranges leading edge has passed and the games are over? Although empirical studies indicate that dispersal propensity attenuates following range expansion, hypotheses about the mechanisms driving this attenuation have not been clearly articulated or tested. Here, we used a simple model of the spatiotemporal dynamics of two phenotypes, one fast and the other slow, to propose that dispersal attenuation beyond preexpansion levels is only possible in the presence of trade-offs between dispersal and life-history traits. The Olympic Village effect ensures that fast dispersers preempt locations far from the ranges previous limits. When trade-offs are absent, this preemptive spatial advantage has a lasting impact, with highly dispersive individuals attaining equilibrium frequencies that are strictly higher than their introduction frequencies. When trade-offs are present, dispersal propensity decays rapidly at all locations. Our models results about the postcolonization trajectory of dispersal evolution are clear and, in principle, should be observable in field studies. We conclude that empirical observations of postcolonization dispersal attenuation offer a novel way to detect the existence of otherwise elusive trade-offs between dispersal and life-history traits

    Without magic bullets: the biological basis for public health interventions against protein folding disorders

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    Protein folding disorders of aging like Alzheimer's and Parkinson's diseases currently present intractable medical challenges. 'Small molecule' interventions - drug treatments - often have, at best, palliative impact, failing to alter disease course. The design of individual or population level interventions will likely require a deeper understanding of protein folding and its regulation than currently provided by contemporary 'physics' or culture-bound medical magic bullet models. Here, a topological rate distortion analysis is applied to the problem of protein folding and regulation that is similar in spirit to Tlusty's (2010a) elegant exploration of the genetic code. The formalism produces large-scale, quasi-equilibrium 'resilience' states representing normal and pathological protein folding regulation under a cellular-level cognitive paradigm similar to that proposed by Atlan and Cohen (1998) for the immune system. Generalization to long times produces diffusion models of protein folding disorders in which epigenetic or life history factors determine the rate of onset of regulatory failure, in essence, a premature aging driven by familiar synergisms between disjunctions of resource allocation and need in the context of socially or physiologically toxic exposures and chronic powerlessness at individual and group scales. Application of an HPA axis model is made to recent observed differences in Alzheimer's onset rates in White and African American subpopulations as a function of an index of distress-proneness

    A Relational Event Approach to Modeling Behavioral Dynamics

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    This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac).

    A survey of statistical network models

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    Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry point to this burgeoning literature. We begin with an overview of the historical development of statistical network modeling and then we introduce a number of examples that have been studied in the network literature. Our subsequent discussion focuses on a number of prominent static and dynamic network models and their interconnections. We emphasize formal model descriptions, and pay special attention to the interpretation of parameters and their estimation. We end with a description of some open problems and challenges for machine learning and statistics.Comment: 96 pages, 14 figures, 333 reference

    Delegated causality of complex systems

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    A notion of delegated causality is introduced here. This subtle kind of causality is dual to interventional causality. Delegated causality elucidates the causal role of dynamical systems at the “edge of chaos”, explicates evident cases of downward causation, and relates emergent phenomena to Gödel’s incompleteness theorem. Apparently rich implications are noticed in biology and Chinese philosophy. The perspective of delegated causality supports cognitive interpretations of self-organization and evolution
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